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What is Mercury Voice?

Mercury embodies a cutting-edge collection of diffusion large language models meticulously crafted to deliver exceptional LLM performance at impressive speeds, capable of processing over 1,000 tokens per second on commercial NVIDIA GPUs for instant AI applications. Engineered for compatibility with OpenAI, these models aim to effortlessly supplant conventional LLMs, making integration into existing AI systems simpler than ever. Notably, Mercury 2.5 emerges as the most advanced reasoning diffusion LLM, specifically designed for complex tasks where high performance and quality are of utmost importance. It features an extensive 260K context window, which facilitates sophisticated reasoning, the use of tools, and organized output, proving useful in a range of applications from rapid coding cycles to the creation of agents, customer support systems, and enterprise-level search capabilities. Furthermore, Mercury Voice is expertly optimized for voice agents, achieving an impressive time-to-first-token of under 170 ms while also supporting reasoning, tool usage, structured outputs, and a 128K context window. This makes it exceptionally adaptable for numerous applications, such as customer support, healthcare assistance, educational platforms, and interactive gaming experiences. In essence, the Mercury family is dedicated to expanding the frontiers of what AI can achieve in real-time scenarios, continuously striving for innovation and excellence. As they push the limits of technology, they open new avenues for enhancing user experiences across diverse sectors.

What is Mercury Edit 2?

Mercury Edit 2 is an advanced AI model developed by Inception Labs, forming part of the Mercury suite, and is designed for efficient reasoning, coding, and editing through a unique architecture that diverges from standard large language models. This model improves upon the capabilities of Mercury 2, a diffusion-based system that can produce and enhance entire outputs at once, as opposed to the traditional approach of generating text token by token, resulting in significantly faster processing and more flexible editing. Rather than serving as a straightforward "typewriter," it functions as a responsive editor, starting with an initial draft and progressively refining it across multiple tokens in tandem, which allows for immediate interaction and rapid iterations in various areas, including code refinement, content generation, and agent-oriented tasks. With a remarkable throughput of nearly 1,000 tokens per second, this framework greatly exceeds the performance of conventional models while maintaining strong reasoning capabilities across a variety of benchmarks. Its innovative structure not only changes how users engage with AI but also establishes a new benchmark for excellence within the realm of artificial intelligence, pushing the boundaries of what is possible in this rapidly evolving field. As a result, it opens up new avenues for creativity and productivity that were previously unattainable.

Media

Media

Integrations Supported

Claude Haiku 4.5
GPT-5.6 Luna
Gemini 3.5 Flash-Lite
OpenAI

Integrations Supported

Cline
Cursor
ElevenLabs
Inception Labs
Kilo Code
LangChain
OpenClaw
OpenCode
Roo Code
Vapi AI
Zed

API Availability

Has API

API Availability

Has API

Pricing Information

$0.04 per 1M tokens
Free Version

Pricing Information

$0.25 per 1M input tokens
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Inception

Company Location

United States

Company Website

www.inceptionlabs.ai/models

Company Facts

Organization Name

Inception

Company Location

United States

Company Website

www.inceptionlabs.ai/blog/introducing-mercury-edit-2

Categories and Features

AI Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

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